Pregled bibliografske jedinice broj: 553103
Estimation of stands parameters from IKONOS satellite images using textural features
Estimation of stands parameters from IKONOS satellite images using textural features // Proceedings of the 7th International Symposium on Image and Signal Processing and Analysis / Lončarić, S. ; Ramponi, G. ; Seršić, D. (ur.).
Zagreb: Fakultet elektrotehnike i računarstva Sveučilišta u Zagrebu, 2011. str. 491-496 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 553103 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Estimation of stands parameters from IKONOS satellite images using textural features
Autori
Klobucar, Damir ; Subašic, Marko ; Pernar, Renata
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 7th International Symposium on Image and Signal Processing and Analysis
/ Lončarić, S. ; Ramponi, G. ; Seršić, D. - Zagreb : Fakultet elektrotehnike i računarstva Sveučilišta u Zagrebu, 2011, 491-496
ISBN
978-953-184-159-7
Skup
7th International Symposium on Image and Signal Processing and Analysis (ISPA 2011)
Mjesto i datum
Dubrovnik, Hrvatska, 04.09.2011. - 06.09.2011
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
artificial neural network; IKONOS satellite images; stands parameters; textural features
Sažetak
We present our research on artificial neural network application in remote sensing analysis of forest management data. The presented research is part of our ongoing investigation of texture analysis application on estimation of stand parameters for the forestry needs. In our investigation we have used IKONOS (PAN 1m x 1m) satellite image. We have used two groups of texture features. The first group is based on first and second order histograms and the second group is based on Fourier transform. We have experimented separately with each feature set and also with both of them combined. We tried radial basis neural networks and multilayer perceptrons with different sets of parameters. Optimal network parameters were calculated and we report results of those optimal neural networks. The stand parameters we were estimating include number of trees, stocking, basal area and volume. Each of the parameters is estimated with its own neural network. Separate estimations are done for VI (121 -140 yrs) and VII (141 – 160 yrs) age class. The experiments have confirmed good estimation accuracy and good correlation with target values.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo, Šumarstvo
POVEZANOST RADA
Projekti:
036-0362214-1989 - Inteligentne metode obrade i analize slika (Lončarić, Sven, MZO ) ( CroRIS)
068-0681966-2786 - Praćenje zdravstvenog stanja šuma metodama daljinskih istraživanja (Pernar, Renata, MZOS ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb,
Fakultet šumarstva i drvne tehnologije
